Software Engineer - Manipulation

Apptronik • Sunnyvale, CA

1d

About The Position

Apptronik is a human-centered robotics company developing AI-powered robots, including its flagship humanoid robot, Apollo. The Software Engineer - Manipulation is a core contributor to the robot’s ability to interact with the world reliably and precisely. The role develops and deploys learning-based manipulation policies, focusing on post-training methods that adapt and improve policies on real tasks and physical hardware. It bridges research and scalable, reliable production software, working with simulation, data, hardware, and systems teams to take policies from demonstration data through post-training to robust deployment across the robot fleet.

The engineer develops visuomotor policies for tasks such as grasping, in-hand manipulation, and whole-arm manipulation, and supports their reliable, low-latency execution on hardware. The role spans simulation and offline evaluation through transfer and fine-tuning on robots, as well as evaluation, regression testing, and ongoing software quality practices.

This is a direct-hire position. The annual salary range is $180,000–$240,000. Apptronik provides equal employment opportunities and prohibits discrimination and harassment based on protected characteristics under applicable law.

Requirements

• MS degree with 3+ years of relevant experience, or a recent PhD, in Robotics, Computer Science, Electrical Engineering, or a related field.
• Relevant experience focused on learning-based manipulation or a closely related area.
• Proven track record of taking learned policies from research or simulation environments and deploying them successfully on physical hardware.
• Strong experience in robotic manipulation, including grasping, in-hand or whole-arm control, and high-DOF motion, with a track record of hardware deployment.
• Hands-on experience training and debugging learned policies, including post-training methods such as RL fine-tuning, distillation, and imitation learning (e.g., DAgger).
• Proficiency in Python, C++, and PyTorch or JAX, with experience building real-time robotic software stacks.
• Experience working with demonstration and teleoperation data and building evaluation pipelines for learned policies.
• Ability to sit for prolonged periods and work at a desk and computer.
• Ability to lift 15 pounds at times.
• Vision to read printed materials and a computer screen; hearing and speech to communicate.

Nice To Haves

• Experience with physics engines such as IsaacSim, MuJoCo, or Drake for policy training and validation.
• Experience adapting large, general-purpose manipulation policies to specific tasks and embodiments.
• Experience with VR/haptic interfaces and retargeting algorithms for human-in-the-loop control.
• Experience integrating tactile/haptic feedback into manipulation pipelines.
• Familiarity with 6D pose estimation, point cloud processing, or visual-servoing.

Responsibilities

• Implement and deploy state-of-the-art learning-based manipulation policies for reliable performance on real-world tasks using physical hardware.
• Adapt and improve policies for new tasks and hardware using post-training methods such as RL fine-tuning, policy distillation, and interactive imitation learning (e.g., DAgger).
• Build and maintain post-training data pipelines, including teleoperation and demonstration collection, retargeting, dataset aggregation, and curation.
• Drive the development cycle from simulation and offline evaluation through robust transfer and fine-tuning on the robot.
• Develop visuomotor policies for grasping, in-hand manipulation, and whole-arm manipulation, with reliable, low-latency hardware execution.
• Define evaluation metrics and regression tests for policy performance in simulation and on hardware, and use results to guide technical decisions.
• Collaborate with simulation, data, hardware, and systems teams to diagnose system-level issues and co-develop solutions.
• Maintain code quality through testing, documentation, and peer code reviews.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level